Current and Emerging 3D Models to Study Breast Cancer

Mechanical effects modulate drug resistance in MCF-7-derived organoids: Insights into the wnt/β-catenin pathway

Addressing drug resistance poses a significant challenge in cancer treatment, as cancer cells develop diverse mechanisms to evade chemotherapy drugs, leading to treatment failure and disease relapse. Three-dimensional (3D) cell culture has emerged as a valuable model for studying drug resistance, although the underlying mechanisms remain elusive. By obtaining a better understanding of drug resistance within the 3D culture environment, we can develop more effective strategies to overcome it and improve the success of cancer treatments. Notably, the physical structure undergoes notable changes in 3D culture, with mechanical effects believed to play a pivotal role in drug resistance. Hence, our study aimed to explore the influence of mechanical effects on drug resistance by analyzing data related to "drug resistance" and "mechanobiology". Through this analysis, we identified β-catenin and JNK1 as potential factors, which were further examined in MCF-7 cells cultivated under both 2D and 3D culture conditions. Our findings demonstrate that β-catenin is activated through canonical and non-canonical pathways and associated with the drug resistance, particularly in organoids obtained under 3D culture.

Validation of a 3D perfused cell culture platform as a tool for humanised preclinical drug testing in breast cancer using established cell lines and patient-derived tissues

3D cell culture models of cancer are currently being developed to recapitulate in vivo physiological conditions and to assess therapeutic responses. However, most models failed to incorporate the biochemical and biophysical stimuli from fluid flow. In this study, a three-dimensional scaffold, SeedEZ was applied within the PerfusionPal perfused culture system to investigate how perfusion, and blood-like oxygen delivery influenced breast cancer cell growth and their responses to a commonly used breast cancer drug tamoxifen. Our results showed that breast cancer cells could be maintained over 3 weeks in PerfusionPal with increased cell viability compared to static 3D culture in fully humanised conditions. This platform also supported examining the effect of tamoxifen on breast cancer cell lines and in primary patient-derived breast cancer samples. Future work is warranted to further the adaption for fully humanised assessment of drug effectiveness in a patient personalized approach with the aim to reduce the burden of animal use in cancer research and increase the degree of human pre-clinical data translation to clinic.

Pharmacological Properties of 4′, 5, 7-Trihydroxyflavone (Apigenin) and Its Impact on Cell Signaling Pathways

Plant bioactive compounds, particularly apigenin, have therapeutic potential and functional activities that aid in the prevention of infectious diseases in many mammalian bodies and promote tumor growth inhibition. Apigenin is a flavonoid with low toxicities and numerous bioactive properties due to which it has been considered as a traditional medicine for decades. Apigenin shows synergistic effects in combined treatment with sorafenib in the HepG2 human cell line (HCC) in less time and statistically reduces the viability of tumor cells, migration, gene expression and apoptosis. The combination of anti-cancerous drugs with apigenin has shown health promoting potential against various cancers. It can prevent cell mobility, maintain the cell cycle and stimulate the immune system. Apigenin also suppresses mTOR activity and raises the UVB-induced phagocytosis and reduces the cancerous cell proliferation and growth. It also has a high safety threshold, and active (anti-cancer) doses can be gained by consuming a vegetable and apigenin rich diet. Apigenin also boosted autophagosome formation, decreased cell proliferation and activated autophagy by preventing the activity of the PI3K pathway, specifically in HepG2 cells. This paper provides an updated overview of apigenin’s beneficial anti-inflammatory, antibacterial, antiviral, and anticancer effects, making it a step in the right direction for therapeutics. This study also critically analyzed the effect of apigenin on cancer cell signaling pathways including the PI3K/AKT/MTOR, JAK/STAT, NF-κB and ERK/MAPK pathways.

Long-term cultured microvascular networks on chip for tumor vascularization research and drug testing

The vascular structure of the tumor microenvironment (TME) plays an essential role in the process of metastasis. In vitro microvascular structures that can be maintained for a long time will greatly promote metastasis research. In this study, we constructed a mimicking breast cancer invasion model based on a microfluidic chip platform, and the maintenance time of the self-assembled microvascular networks significantly improved by culturing with fibroblasts (up to 13 days). Using this model, we quantified the invasion ability of breast cancer cells and angiogenesis sprouts caused by cancer cells, and the intravasation behavior of cancer cells was also observed in sprouts. We found that cancer cells could significantly cause angiogenesis by promoting sprouting behaviors of the self-assembled human umbilical vein endothelial cells, which, in turn, promoted the invasion behavior of cancer cells. The drug test results showed that the drug resistance of the widely used anti-cancer drugs 5-Fluorouracil (5-FU) and Doxorubicin (DOX) in the 3D model was higher than that in the 2D model. Meanwhile, we also proved that 5-FU and DOX had the effect of destroying tumor blood vessels. The anti-angiogenic drug Apatinib (VEGFR inhibitor) enhanced the drug effect of DOX on MDA-MB-231 cells, further proving the promoting effect of angiogenesis on the invasion ability of cancer cells. These results indicate that our model is of great value in reconstructing TME and drug testing in vitro.

Three-Dimensional 3D Culture Models in Gynecological and Breast Cancer Research

Traditional two-dimensional (2D) monolayer cell cultures have long been the gold standard for cancer biology research. However, their ability to accurately reflect the molecular mechanisms of tumors occurring in vivo is limited. Recent development of three-dimensional (3D) cell culture models facilitate the possibility to better recapitulate several of the biological and molecular characteristics of tumors in vivo, such as cancer cells heterogeneity, cell-extracellular matrix interactions, development of a hypoxic microenvironment, signaling pathway activities depending on contacts with extracellular matrix, differential growth kinetics, more accurate drugs response, and specific gene expression and epigenetic patterns. In this review, we discuss the utilization of different types of 3D culture models including spheroids, organotypic models and patient-derived organoids in gynecologic cancers research, as well as its potential applications in oncological research mainly for screening drugs with major physiological and clinical relevance. Moreover, microRNAs regulation of cancer hallmarks in 3D cell cultures from different types of cancers is discussed.

Three-Dimensional Organotypic Cultures Reshape the microRNAs Transcriptional Program in Breast Cancer Cells

The 3D organotypic cultures, which depend on the growth of cells over the extracellular matrix (ECM) used as a scaffold, can better mimic several characteristics of solid cancers that influence tumor biology and the response to drug therapies. Most of our current knowledge on cancer is derived from studies in 2D cultures, which lack the ECM-mediated microenvironment. Moreover, the role of miRNAs that is critical for fine-tuning of gene expression is poorly understood in 3D cultures. The aim of this study was to compare the miRNA expression profiles of breast cancer cells grown in 2D and 3D conditions. On an on-top 3D cell culture model using a basement membrane matrix enriched with laminin, collagen IV, entactin, and heparin-sulfate proteoglycans, the basal B (Hs578T) and luminal (T47D) breast cancer cells formed 3D spheroid-like stellate and rounded mass structures, respectively. Morphological changes in 3D cultures were observed as cell stretching, cell–cell, and cell–ECM interactions associated with a loss of polarity and reorganization on bulk structures. Interestingly, we found prolongations of the cytoplasmic membrane of Hs578T cells similar to tunneled nanotubes contacting between neighboring cells, suggesting the existence of cellular intercommunication processes and the possibility of fusion between spheroids. Expression profiling data revealed that 354 miRNAs were differentially expressed in 3D relative to 2D cultures in Hs578T cells. Downregulated miRNAs may contribute to a positive regulation of genes involved in hypoxia, catabolic processes, and focal adhesion, whereas overexpressed miRNAs modulate genes involved in negative regulation of the cell cycle. Target genes of the top ten modulated miRNAs were selected to construct miRNA/mRNA coregulation networks. Around 502 interactions were identified for downregulated miRNAs, including miR-935/HIF1A and miR-5189-3p/AKT that could contribute to cell migration and the response to hypoxia. Furthermore, the expression levels of miR-935 and its target HIF1A correlated with the expression found in clinical tumors and predicted poor outcomes. On the other hand, 416 interactions were identified for overexpressed miRNAs, including miR-6780b-5p/ANKRD45 and miR-7641/CDK4 that may result in cell proliferation inhibition and cell cycle arrest in quiescent layers of 3D cultures. In conclusion, 3D cultures could represent a suitable model that better resembles the miRNA transcriptional programs operating in tumors, with implications not only in the understanding of basic cancer biology in 3D microenvironments, but also in the identification of novel biomarkers of disease and potential targets for personalized therapies in cancer.

Breast Cancer Patient-Derived Scaffolds Can Expose Unique Individual Cancer Progressing Properties of the Cancer Microenvironment Associated with Clinical Characteristics

Simple Summary

Despite huge progress in cancer diagnostics and medicine we still lack optimal cancer treatments for patients with aggressive diseases. This problem can be influenced by the biological heterogeneity of cancer cells as well as poorly understood cancer promoting effects of the cancer microenvironment being an important part of the cancer niche. In this study we have specifically monitored the activity of the cancer microenvironment in breast cancer patients using cell-free scaffolds repopulated with reporter cancer cells sensing the activity of the patient environment. The data show that scaffold induced changes in epithelial-mesenchymal transition and pluripotency markers were linked to clinical and prognostic properties of the original cancer and the information was even more precise when matching estrogen receptor status in our system. The findings highlight that patient-derived scaffolds uncover important information about varying malignant promoting properties in the cancer niche and can be used as a complementary diagnostic tool.

Abstract

Breast cancer is a heterogeneous disease in terms of cellular and structural composition, and besides acquired aggressive properties in the cancer cell population, the surrounding tumor microenvironment can affect disease progression and clinical behaviours. To specifically decode the clinical relevance of the cancer promoting effects of individual tumor microenvironments, we performed a comprehensive test of 110 breast cancer samples using a recently established in vivo-like 3D cell culture platform based on patient-derived scaffolds (PDSs). Cell-free PDSs were recellularized with three breast cancer cell lines and adaptation to the different patient-based microenvironments was monitored by quantitative PCR. Substantial variability in gene expression between individual PDS cultures from different patients was observed, as well as between different cell lines. Interestingly, specific gene expression changes in the PDS cultures were significantly linked to prognostic features and clinical information from the original cancer. This link was even more pronounced when ERα-status of cell lines and PDSs matched. The results support that PDSs cultures, including a cancer cell line of relevant origin, can monitor the activity of the tumor microenvironment and reveal unique information about the malignancy-inducing properties of the individual cancer niche and serve as a future complementary diagnostic tool for breast cancer.

The decreased serum activity of cytosolic 5'-nucleotidase IA as a potential marker of breast cancer-associated muscle inflammation

Cytosolic 5'-nucleotidase IA (cN-IA) plays a central role in the regulation of the purine nucleotide pool in skeletal muscle, preferentially converting adenosine monophosphate to adenosine. cN-IA can act as an autoantigen in muscle diseases, including the paraneoplastic syndrome related to breast cancer (BC). As a result of myocyte damage, released cN-IA protein may trigger the production of anti-cN-IA antibodies (anti-NT5C1A). This work aimed to develop an effective method to measure cN-IA activity in the serum and analyze it in BC patients. Our study demonstrated that serum cN-IA activity was decreased in BC patients and we assumed it is due to the presence of specific autoantibodies. We found correlations between cN-IA activity and parameters of inflammatory muscle damage. Thus, cN-IA is worth further attention to clarify its usefulness as a biomarker of BC-associated polymyositis.

Identification of Radiomic Features as an Imaging Marker to Differentiate Benign and Malignant Breast Masses Based on Magnetic Resonance Imaging

Background - Breast cancer is one of the most common cancers among women globally and early identification is known to increase patient outcomes. Therefore, the main aim of this study is to identify the essential radiomic features as an image marker and compare the diagnostic feasibility of feature parameters derived from radiomics analysis and conventional Magnetic Resonance Imaging (MRI) to differentiate benign and malignant breast masses.

Methods and Material - T1-weighted Dynamic Contrast-Enhanced (DCE) breast MR axial images of 151 (benign (79) and malignant (72)) patients were chosen. Regions of interest were selected using both manual and semi-automatic segmentation from each lesion. 382 radiomic features computed on the selected regions. A random forest model was employed to detect the most important features that differentiate benign and malignant breast masses. The ten most important radiomics features were obtained from manual and semi-automatic segmentation based on the Gini index to train a support vector machine. MATLAB and IBM SPSS Statistics Subscription software used for statistical analysis.

Results - The accuracy (sensitivity) of the models built from the ten most significant features obtained from manual and semi-automatic segmentation were 0.815 (0.84), 0.821 (0.87), respectively. The top 10 features obtained from manual delineation and semi-automatic segmentation showed a significant difference (p<0.05) between benign and malignant breast lesions.

Conclusion - This radiomics analysis based on DCE-BMRI revealed distinct radiomic features to differentiate benign and malignant breast masses. Therefore, the radiomics analysis can be used as a supporting tool in detecting breast MRI lesions.

Drugs repurposed: An advanced step towards the treatment of breast cancer and associated challenges

Breast cancer (BC) is mostly observed in women and is responsible for huge mortality in women subjects globally. Due to the continued development of drug resistance and other contributing factors, the scientific community needs to look for new alternatives, and drug repurposing is one of the best opportunities. Here we light upon the drug repurposing with a major focus on breast cancer. BC is a division of cancer known as the leading cause of death of 2.3 million women globally, with 685,000 fatalities. This number is steadily rising, necessitating the development of a treatment that can extend survival time. All available treatments for BC are very costly as well as show side effects. This unfulfilled requirement of the anti-cancer drugs ignited an enthusiasm for drug repositioning, which means finding out the anti-cancer use of already marketed drugs for other complications. With the advancement in proteomics, genomics, and computational approaches, the drug repurposing process hastens. So many drugs are repurposed for the BC, including alkylating agents, antimetabolite, anthracyclines, an aromatase inhibitor, mTOR, and many more. The drug resistance in breast cancer is rising, so reviewing how the challenges in breast cancer can be combated with drug repurposing. This paper provides the updated information on all the repurposed drugs candidates for breast cancer with the molecular mechanism responsible for their anti-tumor activity. Additionally, all the challenges that occur during the repurposing of the drugs are discussed.

3D bioprinting: current status and trends—a guide to the literature and industrial practice

The multidisciplinary research field of bioprinting combines additive manufacturing, biology and material sciences to create bioconstructs with three-dimensional architectures mimicking natural living tissues. The high interest in the possibility of reproducing biological tissues and organs is further boosted by the ever-increasing need for personalized medicine, thus allowing bioprinting to establish itself in the field of biomedical research, and attracting extensive research efforts from companies, universities, and research institutes alike. In this context, this paper proposes a scientometric analysis and critical review of the current literature and the industrial landscape of bioprinting to provide a clear overview of its fast-changing and complex position. The scientific literature and patenting results for 2000–2020 are reviewed and critically analyzed by retrieving 9314 scientific papers and 309 international patents in order to draw a picture of the scientific and industrial landscape in terms of top research countries, institutions, journals, authors and topics, and identifying the technology hubs worldwide. This review paper thus offers a guide to researchers interested in this field or to those who simply want to understand the emerging trends in additive manufacturing and 3D bioprinting.

Graphic abstract

Anticancer Activity and Mechanism of Action Evaluation of an Acylhydrazone Cu(II) Complex toward Breast Cancer Cells, Spheroids, and Mammospheres

The purpose of this work was to screen the anticancer activity and mechanisms of action of Cu(II)-acylhydrazone complex [Cu(HL)(H₂ O)](NO₃ )⋅H₂ O, (CuHL), to find a potential novel agent for breast chemotherapies. Cytotoxicity studies on MCF7 cells demonstrated that CuHL has stronger anticancer properties than cisplatin over breast cancer cell models. Computational simulations showed that CuHL could interact in the minor groove of the DNA dodecamer, inducing a significant genotoxic effect on both cancer cells from 0.5 to 1 μM. In this sense, molecular docking and molecular dynamics simulations showed that the compound could interact with 20S proteasome subunits. Also, cell proteasome experiments using breast cancer cells revealed that the complex can inhibit proteasomal activity. Moreover, CuHL induced apoptosis in breast cancer cells at very low micromolar concentrations (0.5-2.5 μM) and displayed relevant anticancer activity over spheroids derived from MCF7 cells. Ultimately, CuHL diminished the number of mammospheres formed, disturbing their morphology and size.

Integrating Quantitative Assays with Biologically Based Mathematical Modeling for Predictive Oncology

We provide an overview on the use of biological assays to calibrate and initialize mechanism-based models of cancer phenomena. Although artificial intelligence methods currently dominate the landscape in computational oncology, mathematical models that seek to explicitly incorporate biological mechanisms into their formalism are of increasing interest. These models can guide experimental design and provide insights into the underlying mechanisms of cancer progression. Historically, these models have included a myriad of parameters that have been difficult to quantify in biologically relevant systems, limiting their practical insights. Recently, however, there has been much interest calibrating biologically based models with the quantitative measurements available from (for example) RNA sequencing, time-resolved microscopy, and in vivo imaging. In this contribution, we summarize how a variety of experimental methods quantify tumor characteristics from the molecular to tissue scales and describe how such data can be directly integrated with mechanism-based models to improve predictions of tumor growth and treatment response.